Impact of study design on vaccine effectiveness estimates of 2 mRNA COVID-19 vaccine doses in patients with stage 5 chronic kidney disease
Authors: Kyla L. Naylor, Eric McArthur, Stephanie N. Dixon, Jeffrey C. Kwong, Doneal Thomas, Shabnam Balamchi, Peter G. Blake, Amit X. Garg, Mohammad Atiquzzaman, Michelle A. Hladunewich, Adeera Levin, Angie Yeung, Matthew J. Oliver
Journal: Kidney International (2023)

In observational studies, the World Health Organization recommends the test-negative design (TND) to assess corona virus disease 2019 (COVID-19) vaccine effectiveness (VE), due its accuracy and efficiency.1World Health OrganizationEvaluation of COVID-19 vaccine effectiveness.https://www.who.int/publications/i/item/WHO-2019-nCoV-vaccine_effectiveness-measurement-2021.1Date accessed: May 17, 2022Google Scholar The TND is a variation of the case–control design that restricts the study population to individuals who are tested for severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) and have symptoms consistent with COVID-19.2Chung H. He S. Nasreen S. et al.Effectiveness of BNT162b2 and mRNA-1273 covid-19 vaccines against symptomatic SARS-CoV-2 infection and severe covid-19 outcomes in Ontario, Canada: test negative design study.BMJ. 2021; 374: n1943Crossref PubMed Scopus (171) Google Scholar Although this design helps reduce bias resulting from differences in healthcare-seeking behavior,1World Health OrganizationEvaluation of COVID-19 vaccine effectiveness.https://www.who.int/publications/i/item/WHO-2019-nCoV-vaccine_effectiveness-measurement-2021.1Date accessed: May 17, 2022Google Scholar a major barrier when using administrative healthcare data is the requirement for individuals who are tested for SARS-CoV-2 infection to fulfill a specific case definition (i.e., being symptomatic), which requires symptom data to be well recorded. This approach presents particular challenges for smaller specialized populations, such as individuals with stage 5 chronic kidney disease (CKD), as the requirement for symptom information may further decrease an already limited sample size. The vaccine literature suggests that effectiveness estimates in the general population may vary by study design.1World Health OrganizationEvaluation of COVID-19 vaccine effectiveness.https://www.who.int/publications/i/item/WHO-2019-nCoV-vaccine_effectiveness-measurement-2021.1Date accessed: May 17, 2022Google Scholar,3Crowcroft N.S. Schwartz K.L. Savage R.D. et al.A call for caution in use of pertussis vaccine effectiveness studies to estimate waning immunity: a Canadian Immunization Research Network study.Clin Infect Dis. 2021; 73: 83-90Crossref PubMed Scopus (6) Google Scholar However, to our knowledge, no studies using the same population and time period have evaluated the impact of study design on COVID-19 VE estimates in the CKD population, and no study has used the TND. In this study, we examined the VE of 2 doses of mRNA COVID-19 vaccines (compared to unvaccinated individuals) against SARS-CoV-2 infection and severe outcomes (hospitalization and death) using 3 study designs (i.e., the TND and pseudo-TND [pTND], which was restricted to individuals tested for SARS-CoV-2 infection, with the former, which was restricted to individuals with recorded symptoms; and a cohort design) in patients with stage 5 CKD. We conducted this study using linked population-based administrative healthcare databases from Ontario, Canada held at ICES (ices.on.ca). We started with 14,416 individuals with stage 5 CKD who had a total of 40,511 tests for SARS-CoV-2 (with or without recorded COVID-19 symptoms) from January 11, 2021 (earliest date an individual could have received a second dose) to November 30, 2021. Approximately 6% of all tests in our population had recorded symptoms consistent with COVID-19 at the time of testing. In brief, the TND included 1202 individuals (74 test-positive cases and 1128 test-negative controls; Supplementary Figure S1A), and when examining severe outcomes, 1348 individuals were included with 220 test-positive severe outcome cases (Supplementary Figure S1B). For the pTND, we included 8127 individuals (402 test-positive cases and 7725 test-negative controls; Supplementary Figure S1C), and for severe outcomes, we included 7945 individuals with 220 test-positive severe outcome cases (Supplementary Figure S1D). In the cohort design, we included 14,416 individuals (Supplementary Figure S1E), with 742 (5.1%) testing positive for SARS-CoV-2, of which 427 (59.8%) either were hospitalized or died, over a median follow-up of 351 days (25th, 75th percentile: 290, 351). Please see the Supplementary Methods, Supplementary Appendix S1, Supplementary Appendix S2, and the Supplementary Results for further information. Table 1 displays differences between individuals with 2 COVID-19 vaccine doses and those unvaccinated. Supplementary Table S1 demonstrates differences between cases and controls in the TND and pTND. The most common vaccine combination across design types was receipt of 2 doses of BNT162b2 (>65% across design types; Supplementary Table S2).Table 1Baseline characteristics for the test-negative, pseudo-test-negative, and cohort study designs for patients with stage 5 chronic kidney disease presented by vaccination status between December 14, 2020 and November 30, 2021Test-negative (n = 1202)Pseudo-test-negative (n = 8127)Cohort (n = 14,416)Vaccination statusaVaccination status ascertained prior to index date (i.e., SARS-CoV-2 test date).Standardized differencebA standardized difference value >0.1 is considered a meaningful difference and is presented in bold font.Vaccination statusaVaccination status ascertained prior to index date (i.e., SARS-CoV-2 test date).Standardized differencebA standardized difference value >0.1 is considered a meaningful difference and is presented in bold font.Vaccination statuscVaccination status represents the vaccination status at the end of follow-up.Standardized differencebA standardized difference value >0.1 is considered a meaningful difference and is presented in bold font.Characteristic2 doses of mRNA vaccine (n = 650)Unvaccinated (n = 552)2 doses of mRNA vaccine (n = 4266)Unvaccinated (n = 3861)At least 1 dose of mRNA vaccine (n = 11,852)Unvaccinated (n = 2564)Age, yr68.22 ± 14.4464.05 ± 15.470.2868.93 ± 14.0166.67 ± 14.920.1668.59 ± 14.2467.83 ± 15.240.05F291 (44.8)246 (44.6)0.001799 (42.2)1659 (43.0)0.025073 (42.8)1130 (44.1)0.03Neighborhood income quintiledNeighborhood income is displayed as quintiles of average neighborhood income. Data were missing for <1% of the population and were included in income quintile 3.1 (low)222 (34.2)186 (33.7)0.011311 (30.7)1198 (31.0)0.013377 (28.5)828 (32.3)0.082139 (21.4)123 (22.3)0.02885 (20.7)873 (22.6)0.052584 (21.8)593 (23.1)0.033 (middle)107 (16.5)101 (18.3)0.05843 (19.7)754 (19.5)0.012363 (19.9)494 (19.3)0.024101 (15.5)84 (15.2)0.01687 (16.1)573 (14.8)0.031945 (16.4)338 (13.2)0.095 (high)81 (12.5)58 (10.5)0.06540 (12.7)463 (12.0)0.021583 (13.4)311 (12.1)0.04RuraleRural residence was defined as residing in an area with a population size <10,000.86 (13.2)91 (16.5)0.09382 (9.0)454 (11.8)0.091243 (10.5)267 (10.4)0.00Mo/Q of SARS-CoV-2 testJan 2021 (Q for TND: Jan–Mar 2021)30 (4.6)425 (77.0)2.181–5 (0.0–0.1)fIn accordance with ICES policy of suppressing cell sizes <6, numbers are presented as ranges.1144–1148 (29.6–29.7)fIn accordance with ICES policy of suppressing cell sizes <6, numbers are presented as ranges.0.91–0.92fIn accordance with ICES policy of suppressing cell sizes <6, numbers are presented as ranges.Feb 202182–86 (1.9–2.0)fIn accordance with ICES policy of suppressing cell sizes <6, numbers are presented as ranges.1031–1035 (26.7–26.8)fIn accordance with ICES policy of suppressing cell sizes <6, numbers are presented as ranges.0.75–0.76fIn accordance with ICES policy of suppressing cell sizes <6, numbers are presented as ranges.Mar 2021150 (3.5)893 (23.1)0.60Apr 2021 (Q for TND: Apr–June 2021)175 (26.9)79 (14.3)0.32421 (9.9)360 (9.3)0.02May 2021478 (11.2)138 (3.6)0.29June 2021583 (13.7)76 (2.0)0.45July 2021 (Q for TND: July–Sept 2021)357 (54.9)38 (6.9)1.22499 (11.7)49 (1.3)0.43Aug 2021505 (11.8)36 (0.9)0.46Sept 2021498 (11.7)53 (1.4)0.43Oct 2021 (Q for TND: Oct. to end of Nov 2021)88 (13.5)10 (1.8)0.45530 (12.4)35 (0.9)0.47Nov 2021515 (12.1)42 (1.1)0.45ComorbiditiesCCIgEveryone received a minimum score of 2 for the CCI, as the index assigns anyone with kidney disease a minimum score of 2. Therefore, anyone with a score of 0 was given a score of 2, and anyone with a score of 1 was given a score of 3.3.92 ± 1.823.92 ± 1.820.003.69 ± 1.723.73 ± 1.740.023.48 ± 1.653.74 ± 1.870.15CHD381 (58.6)322 (58.3)0.012371 (55.6)2113 (54.7)0.025866 (49.5)1385 (54.0)0.09HT618 (95.1)516 (93.5)0.074076 (95.5)3634 (94.1)0.0711,120 (93.8)2398 (93.5)0.01DB474 (72.9)390 (70.7)0.052951 (69.2)2621 (67.9)0.037667 (64.7)1680 (65.5)0.02Major cancerhMajor cancer included the following: lung/bronchi, colon/rectum, breast, pancreas, prostate, leukemia, non-Hodgkin lymphoma, liver, ovarian, and esophageal.98 (15.1)92 (16.7)0.04711 (16.7)623 (16.1)0.011901 (16.0)443 (17.3)0.03Dialysis vintage,iIn accordance ICES policy of suppressing cell sizes <6, the dialysis vintage categories for the TND were collapsed into 1 category—“dialysis.” yrPre-dialysis, 0116 (17.8)118 (21.4)0.09782 (18.4)911 (23.6)0.132997 (25.3)843 (32.9)0.17>0 to 13118 (73.1)2676 (69.3)0.008036 (67.8)1592 (62.1)0.01>1366 (8.6)274 (7.1)0.02819 (6.9)129 (5.0)0.01Dialysis534 (82.1)434 (78.6)0.09ModalityeGFR <15 ml/min per 1.73 m2116 (17.8)118 (21.4)0.09782 (18.4)911 (23.6)0.132997 (25.3)843 (32.9)0.17In-center MD419 (64.5)309 (56.0)0.172745 (64.3)2285 (59.2)0.116509 (54.9)1165 (45.4)0.19Home MD115 (17.7)125 (22.6)0.12739 (17.3)665 (17.2)0.002346 (19.8)556 (21.7)0.05LTC residence77 (11.8)14 (2.5)0.37290 (6.8)93 (2.4)0.21399 (3.4)113 (4.4)0.05No. tests within 3 mo prior to Dec 14, 20201.28 ± 2.330.91 ± 1.600.190.94 ± 1.980.83 ± 1.600.070.66 ± 1.550.78 ± 1.700.07PHU regionjPHU region was missing for <1% of individuals, and missing data were included in the Central West Region.Central West292 (6.8)243 (5.6)0.02814 (6.9)159 (6.2)0.03Central East774 (18.1)599 (15.5)0.072034 (17.2)448 (17.5)0.01Durham182 (4.3)171 (4.4)0.01571 (4.8)116 (4.5)0.01Eastern241 (5.6)240 (6.2)0.02739 (6.2)152 (5.9)0.01North331 (7.8)440 (11.4)0.12971 (8.2)200 (7.8)0.01Ottawa199 (4.7)145 (3.8)0.05635 (5.4)118 (4.6)0.03Peel487 (11.4)424 (11.0)0.011347 (11.4)310 (12.1)0.02South West279 (6.5)567 (14.7)0.271153 (9.7)275 (10.7)0.03Toronto (TND was residing in the Greater Toronto Area)257 (39.5)219 (39.7)0.001156 (27.1)817 (21.2)0.142724 (23.0)643 (25.1)0.05York325 (7.6)215 (5.6)0.08864 (7.3)143 (5.6)0.07Dose 2 to test date, d98.16 ± 61.2091.06 ± 62.96Apr, April; Aug, August; Feb, February; CCI, Charlson Comorbidity Index; CHD, Chronic Heart Disease; DB, diabetes; Dec, December; eGFR, estimated glomerular filtration rate; F, female; HT, hypertension; Jan, January; LTC, long-term care; Mar, March; MD, maintenance dialysis; Nov, November; Oct, October; PHU, public health unit; Q, quarter; Sept, September; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2; TND, test-negative design.Data are presented as n (%) or mean ± SD.a Vaccination status ascertained prior to index date (i.e., SARS-CoV-2 test date).b A standardized difference value >0.1 is considered a meaningful difference and is presented in bold font.c Vaccination status represents the vaccination status at the end of follow-up.d Neighborhood income is displayed as quintiles of average neighborhood income. Data were missing for <1% of the population and were included in income quintile 3.e Rural residence was defined as residing in an area with a population size <10,000.f In accordance with ICES policy of suppressing cell sizes <6, numbers are presented as ranges.g Everyone received a minimum score of 2 for the CCI, as the index assigns anyone with kidney disease a minimum score of 2. Therefore, anyone with a score of 0 was given a score of 2, and anyone with a score of 1 was given a score of 3.h Major cancer included the following: lung/bronchi, colon/rectum, breast, pancreas, prostate, leukemia, non-Hodgkin lymphoma, liver, ovarian, and esophageal.i In accordance ICES policy of suppressing cell sizes <6, the dialysis vintage categories for the TND were collapsed into 1 category—“dialysis.”j PHU region was missing for <1% of individuals, and missing data were included in the Central West Region. Open table in a new tab Apr, April; Aug, August; Feb, February; CCI, Charlson Comorbidity Index; CHD, Chronic Heart Disease; DB, diabetes; Dec, December; eGFR, estimated glomerular filtration rate; F, female; HT, hypertension; Jan, January; LTC, long-term care; Mar, March; MD, maintenance dialysis; Nov, November; Oct, October; PHU, public health unit; Q, quarter; Sept, September; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2; TND, test-negative design. Data are presented as n (%) or mean ± SD. VE against infection after 2 doses was 67% (95% confidence interval [CI]: 29%–84%) for the TND, 70% (95% CI: 58%–78%) for the pTND, and 60% (95% CI: 46%–71%) for the cohort design (Figure 1). VE against severe outcomes was 84% (95% CI: 73%–91%) for the TND, 84% (95% CI: 75%–90%) for the pTND, and 72% (95% CI: 59%–81%) for the cohort design. VE estimates using the cohort design were sensitive to multivariable adjustment. For example, the unadjusted VE estimate against infection was 41% (95% CI: 19%–57%) and changed to 60% (95% CI: 46%–71%) after adjustment, whereas for the pTND, the unadjusted and adjusted estimates were 71% (95% CI: 63%–77%) and 70% (95% CI: 58%–78%), respectively. VE estimates using the cohort design were also sensitive to how the nonproportionality of adjustment variables was handled when examining severe outcomes. Supplementary Table S3 provides a summary of all study designs, including strengths and weaknesses. VE estimates for severe outcomes for the TND and the pTND were similar to the main analysis results after restricting test-negative controls to individuals who were hospitalized or died (Figure 1). To our knowledge, this is the first population-level observational study evaluating COVID-19 VE among patients with CKD using 3 different study designs. Our findings indicate that although the magnitude of the VE estimates against SARS-CoV-2 infection and severe outcomes after 2 doses of mRNA vaccines varied across the 3 different designs (TND, pTND, and cohort), ranging from 60% to 70% for infection, and from 72% to 84% for severe outcomes, overall conclusions were consistent. The TND is considered the least-biased and most-efficient study design to evaluate VE, owing to reasons such as reduction of bias arising from differences in healthcare-seeking behaviors, and it is commonly used in the general population.1World Health OrganizationEvaluation of COVID-19 vaccine effectiveness.https://www.who.int/publications/i/item/WHO-2019-nCoV-vaccine_effectiveness-measurement-2021.1Date accessed: May 17, 2022Google Scholar However, a major barrier to using the TND is the requirement for recorded symptom information, which may not be readily available in administrative healthcare databases and may substantially reduce sample size. In our study, we had 14,416 individuals with stage 5 CKD, a number that was reduced to 1202 individuals in the TND. The large reduction in sample size resulted in less-precise estimates and made adjustment for relevant covariates difficult, with concerns for model overfitting. Another consideration for the TND is that the stage 5 CKD population has a high background burden of symptoms (regardless of infection status).4Sniekers D.C. Jung J.K.H. Blake P.G. et al.Province-wide prevalence testing for SARS-CoV-2 of in-center hemodialysis patients and staff in Ontario, Canada: a cross-sectional study.Can J Kidney Heal Dis. 2021; 820543581211036213PubMed Google Scholar,5Murtagh F.E.M. Addington-Hall J. Higginson I.J. The prevalence of symptoms in end-stage renal disease: a systematic review.Adv Chronic Kidney Dis. 2007; 14: 82-99Abstract Full Text Full Text PDF PubMed Scopus (670) Google Scholar Sniekers et al. found that approximately 17% of patients receiving dialysis reported common COVID-19 symptoms (e.g., fatigue) regardless of infection status. The in-center dialysis population is often tested and screened as part of the center’s protocol, rather than letting individuals seek a test on their own; therefore, the bias introduced by differences in healthcare-seeking behaviors may be minimal in this population.4Sniekers D.C. Jung J.K.H. Blake P.G. et al.Province-wide prevalence testing for SARS-CoV-2 of in-center hemodialysis patients and staff in Ontario, Canada: a cross-sectional study.Can J Kidney Heal Dis. 2021; 820543581211036213PubMed Google Scholar,6Ioannidis J.P.A. Factors influencing estimated effectiveness of COVID-19 vaccines in non-randomised studies.BMJ Evidence-Based Med. 2022; 6: 324-329Crossref Scopus (15) Google Scholar,7Yau K. Muller M.P. Lin M. et al.COVID-19 outbreak in an urban hemodialysis unit.Am J Kidney Dis. 2020; 76: 690-695Abstract Full Text Full Text PDF PubMed Scopus (61) Google Scholar This minimization of bias might be the reason we saw similar VE estimates between the TND and the pTND, a finding that is often not seen in the general population. In our study, the cohort design was not as robust as the TND and the pTND, having wide confidence intervals, estimates that were sensitive to covariate adjustment (potentially suggesting greater residual confounding), and several covariates that violated the proportional hazards assumption. Further complicating the use of the cohort design is concern about competing risks, with existing methodology used to account for competing risks (e.g., the Fine and Gray model) having limitations when used with time-varying covariates.8Austin P.C. Aurélien Latouche J.P.F. A review of the use of time-varying covariates in the Fine-Gray subdistribution hazard competing risk regression model.Stat Med. 2020; 39: 103-113Crossref PubMed Scopus (49) Google Scholar In our study, the cohort design consistently produced the lowest VE estimates, which could be due to vaccinated individuals being more likely to seek healthcare and thus more likely to be cases1World Health OrganizationEvaluation of COVID-19 vaccine effectiveness.https://www.who.int/publications/i/item/WHO-2019-nCoV-vaccine_effectiveness-measurement-2021.1Date accessed: May 17, 2022Google Scholar; however, unlike in the general population, in the in-center dialysis population, testing is commonly performed. Furthermore, the TND and the pTND differ from the cohort design in additional ways, which could help explain the variability in VE estimates across design types. For example, the cohort design includes all patients with CKD (i.e., tested and not tested). Additionally, since the cohort design incorporates an individual’s entire follow-up, from index date onward, vaccination status was modelled as a time-varying exposure (unvaccinated, to 1 dose, to 2 doses), whereas the TND and pTND compared only those with 0 versus 2 doses at the time of their test. Our study found similar VE estimates using the TND and the pTND, suggesting that the pTND might be a good study-design choice in the stage 5 CKD population. The pTND has several potential advantages in this population, including having no requirement for symptom information, thereby potentially maximizing sample size, and the computational ease compared to that of the cohort design. We found several between-study differences in the characteristics of vaccinated versus unvaccinated individuals and between cases versus controls across study designs. Although we adjusted for most of these characteristics, unmeasured differences could be present that result in differences in VE estimates across study designs. These differences also highlight how different designs, even within a single population, may produce different study populations, which could affect VE estimates, interpretability, and generalizability of results. This work has some limitations. First, residual confounding may be present across all designs (e.g., differences in healthcare-seeking behaviors). Second, due to our sample size, we were not able to perform any subgroup analyses (e.g., vaccine type), and our confidence intervals were relatively wide. Third, despite our using the same population and timeframe to compare VE estimates, the inherent differences across study designs are important to consider when interpreting results. Last, as do all diagnostic tests, the real-time polymerase chain reaction test for SARS-CoV-2 has imperfect sensitivity and specificity, potentially resulting in misclassification. In conclusion, although VE estimates varied across study designs in the CKD population, overall conclusions were consistent. Results suggest that the pTND might be suitable to estimate VE in the CKD population. Our results highlight the need for clinicians and policymakers to cautiously interpret VE estimates from observational study designs, with considerations for potential biases that could impact VE. MJO is a contracted Medical Lead at Ontario Renal Network, Ontario Health; is the owner of Oliver Medical Management Inc., which licenses Dialysis Management Analysis and Reporting System software; and has received honoraria for speaking from Baxter Healthcare. SB, DT, and AY are salaried employees of Ontario Health. All the other authors declared no competing interests. The results presented in this paper have not been published previously in whole or part. The dataset from this study is held securely in coded form at ICES. Although legal data-sharing agreements between ICES and data providers (e.g., healthcare organizations and government) prohibit ICES from making the dataset publicly available, access may be granted to those who meet prespecified criteria for confidential access, available at www.ices.on.ca/DAS (e-mail: [email protected]). The full Dataset Creation Plan and underlying analytic code are available from the authors upon request, with the understanding that the computer programs may rely upon coding templates or macros that are unique to ICES and therefore are either inaccessible or may require modification. This project was funded by the COVID-19 Immunity Task Force (grant 2122-HQ-000071). The analyses, conclusions, opinions and statements expressed herein are solely those of the authors and do not reflect those of the funding sources; no endorsement is intended or should be inferred. This study was supported by ICES, which is funded by an annual grant from the Ontario Ministry of Health (MOH) and the Ministry of Long-Term Care (MLTC). The study was completed at the ICES Western site, where core funding is provided by the Academic Medical Organization of Southwestern Ontario, the Schulich School of Medicine and Dentistry, Western University, and the Lawson Health Research Institute. The analyses, conclusions, opinions, and statements expressed herein are solely those of the authors and do not reflect those of the funding sources; no endorsement is intended or should be inferred. Parts of this material are based on data and/or information compiled and provided by the Canadian Institute for Health Information (CIHI) and the Ontario Ministry of Health. The analyses, conclusions, opinions, and statements expressed herein are solely those of the authors and do not reflect those of the funding or data sources; no endorsement is intended or should be inferred. Parts of this material are based on data and information provided by Ontario Health (OH). The opinions, results, view, and conclusions reported in this paper are those of the authors and do not necessarily reflect those of OH. No endorsement by OH is intended or should be inferred. The authors thank Hannah Chung for her content expertise. This document used data adapted from the Statistics Canada Postal CodeOM Conversion File, which is based on data licensed from Canada Post Corporation, and/or data adapted from the Ontario Ministry of Health Postal Code Conversion File, which contains data copied under license from ©Canada Post Corporation and Statistics Canada. Download .docx (.16 MB) Help with docx files Supplementary File (Word) Supplementary Methods. Supplementary Appendix S1. The REporting of studies Conducted using Observational, Routinely collected Health Data (RECORD) statement. Supplementary Appendix S2. Coding definition for inclusion criteria, exclusion criteria, and baseline characteristics. Supplementary Results. Supplementary Table S1. Baseline characteristics for the test-negative and pseudo-test-negative designs for patients with stage 5 chronic kidney disease (CKD) presented by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection status. Supplementary Table S2. Coronavirus disease 2019 (COVID-19) vaccine combinations among patients with stage 5 chronic kidney disease (CKD) who received 2 COVID-19 vaccine doses, presented by study design type (test-negative, pseudo-test-negative, and cohort). Supplementary Table S3. Comparison of the test-negative, pseudo-test-negative, and cohort study designs to estimate coronavirus disease 2019 (COVID-19) vaccine effectiveness among individuals with stage 5 chronic kidney disease (CKD). Supplementary References. Supplementary Figure S1. (A) Patients with stage 5 chronic kidney disease (CKD) with recorded coronavirus disease 2019 (COVID-19) symptoms at the time of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing (January 11, 2021 to November 30, 2021) included in the test-negative design (B). Patients with stage 5 CKD who had a severe outcome (i.e., hospitalization or death) associated with a positive SARS-CoV-2 test, or patients who tested negative for SARS-CoV-2 infection with recorded COVID-19 symptoms at the time of SARS-CoV-2 testing (January 11, 2021 to November 30, 2021) who were included in the test-negative study design for severe outcomes associated with a positive SARS-CoV-2 test. (C) Patients with stage 5 CKD with or without recorded COVID-19 symptoms at the time of SARS-CoV-2 testing (January 11, 2021 to November 30, 2021) who were included in the pseudo-test-negative study design. (D) Patients with stage 5 CKD who had a severe outcome (i.e., hospitalization or death) associated with a positive SARS-CoV-2 test or patients who tested negative for SARS-CoV-2 infection at the time of SARS-CoV-2 testing (January 11, 2021 to November 30, 2021) who were included in the pseudo-test-negative study design for severe outcomes associated with a positive SARS-CoV-2 test. (E) Patients with stage 5 CKD who were included in the cohort design.